Existing network management systems used within the context of, illustratively, network operations centers (NOCs) provide to operators a visualization of virtual or nonvirtual elements within a deployed communication network or data center. This visualization can be graphically manipulated by the user to provide various management functions. However, while useful, existing network management systems typically require significant human knowledge of the communication network or data center topology as well as the likely sources of failure or operational degradation.
Currently, the network operator relies on filtered and sorted alarm lists, Network Maps, as well as physical alarm LEDs and indications on equipment to determine which NEs to trouble shoot first. These methods require the user to sort through tens/hundreds of thousands of alarms and still will not always indicate which NE needs the most attention. The judgment of the user is required to determine which NE is investigated first.
Specifically, presented with an undesired operational mode, a skilled operator in the NOC (or remotely accessing a management system) may understand what type of elements or sub-elements within the communication network or data center are likely the cause of the failure or undesired operational mode and, thus, can then address the failure or the undesired operational mode.
Unfortunately, few have the necessary knowledge or skills for this task. Further, the enormous amount of alarms, warnings and other information generated by the (typically) thousands of elements within a communication network or data center is difficult for even the most skilled operator to manage in a timely manner.